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TVL1 Shape Approximation from Scattered 3D Data

Funk, Eugen und Börner, Anko und Dooley, Laurence (2015) TVL1 Shape Approximation from Scattered 3D Data. In: 10th International Conference on Computer Vision Theory and Applications, VISAPP 2015. Springer. International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Berlin. doi: 10.5220/0005301802940304.

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Kurzfassung

With the emergence in 3D sensors such as laser scanners and 3D reconstruction from cameras, large 3D point clouds can now be sampled from physical objects within a scene. The raw 3D samples delivered by these sensors however, contain only a limite d degree of information about the environment the objects exist in, which means that further geometrical high-level modelling is essential. In addition, issues like sparse data measurements, noise, missing samples due to occlusion, and the inherently huge datasets involved in such representations makes this task extremely challenging. This paper addresses these issues by presenting a new 3D shape modelling framework for samples acquired from 3D sensor. Motivated by the success of nonlinear kernel-based approximation techniques in the statistics domain, existing methods using radial basis functions are applied to 3D object shape approximation. The task is framed as an optimization problem and is extended using non-smooth L1 total variation regularization. Appropriate convex energy functionals are constructed and solved by applying the Alternating Direction Method of Multipliers approach, which is then extended using Gauss-Seidel iterations. This significantly lowers the computational complexity involved in generating 3D shape from 3D samples, while both numerical and qualitative analysis confirms the superior shape modelling performance of this new framework compared with existing 3D shape reconstruction techniques.

elib-URL des Eintrags:https://elib.dlr.de/100369/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:TVL1 Shape Approximation from Scattered 3D Data
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Funk, EugenOS-ISNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Börner, AnkoOS-ISNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Dooley, LaurenceOpen UniversityNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:11 März 2015
Erschienen in:10th International Conference on Computer Vision Theory and Applications, VISAPP 2015
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Nein
DOI:10.5220/0005301802940304
Verlag:Springer
Name der Reihe:LNCS - Lecture notes on computer science
Status:veröffentlicht
Stichwörter:Shape Reconstruction, Radial Basis Function Interpolation, L1 Total Variation Minimization, Iterative Large Scale Optimization
Veranstaltungstitel:International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Veranstaltungsort:Berlin
Veranstaltungsart:internationale Konferenz
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Bodengebundener Verkehr (alt)
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V BF - Bodengebundene Fahrzeuge
DLR - Teilgebiet (Projekt, Vorhaben):V - Fahrzeugintelligenz (alt), R - Robotische Exploration (alt), R - Vorhaben Intelligente Mobilität (alt)
Standort: Berlin-Adlershof
Institute & Einrichtungen:Institut für Optische Sensorsysteme > Informationsverarbeitung OS
Hinterlegt von: Funk, Eugen
Hinterlegt am:07 Dez 2015 07:09
Letzte Änderung:17 Jul 2023 15:00

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